Deformable Models: Theory and Biomaterial Applications

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Aly Farag
Springer Science & Business Media, Aug 10, 2007 - Technology & Engineering - 581 pages
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In the biomedical field, biomedical imagery has come to be a discipline of its own, given the nature of its applications in the understanding of the human body and medical diagnostics. The understanding of Deformable Models are the significant utility on biomedical imagery primarily because of its ability to perform efficient topology preservation and fast shape recovery. This has dominated the binary, grayscale and color imaging frameworks, which the eye can perceive. It has not only the ability to find boundaries and surfaces that are deep-seated in 2-D and 3-D volumes respectively, but also provide satisfactory solutions for the completion of cognitive objects with missing boundaries.

Deformable Models: Theory and Biomaterial Applications focuses on the core image processing techniques: theory and biomaterials useful to research and industry.

 

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Contents

2 ANALYSIS OF CURRENT GEOMETRIC SNAKES
292
3 STOP AND GO FORMULATION
294
4 DEFORMABLE MODELS IN THE CLASSIFICATION PIPELINE
297
5 STOP AND GO SNAKES DESIGN
312
6 EXPERIMENTAL RESULTS
313
7 CONCLUSIONS
321
8 ACKNOWLEDGMENTS
322
DEFORMABLE MODELBASED SEGMENTATION OF THE PROSTATE FROM ULTRASOUND IMAGES
325

8 CONCLUSIONS AND FUTURE WORK
26
PARAMETRIC CONTOUR MODEL IN MEDICAL IMAGE SEGMENTATION
31
1 INTRODUCTION
32
THEORY
35
3 ACTIVE CONTOUR EVOLUTION
40
4 APRIORI INFORMATION
53
5 TOPOLOGICAL SNAKE
62
6 DISCUSSION AND CONCLUSIONS
64
7 REFERENCES
71
DEFORMABLE MODELS AND THEIR APPLICATION IN SEGMENTATION OF IMAGED PATHOLOGY SPECIMENS
75
2 MATHEMATICAL BACKGROUND OF DEFORMABLE MODELS
79
3 PARAMETRIC DEFORMABLE MODELS
82
4 GEODESIC OR LEVEL SETBASED DEFORMABLE MODELS
87
5 CONCLUDING REMARKS
91
6 ACKNOWLEDGMENTS
93
IMAGE SEGMENTATION USING THE LEVEL SET METHOD
95
1 INTRODUCTION
96
2 RELATED WORK
97
3 LEVEL SET METHODS AND IMAGE SEGMENTATION
100
4 AUGMENTING THE SPEED FUNCTION
108
5 SEMIAUTOMATIC SEGMENTATION AND TRACKING OF SERIAL MEDICAL IMAGES
115
6 CONCLUSION
118
7 ACKNOWLEDGMENTS
120
PARALLEL COVOLUME SUBJECTIVE SURFACE METHOD FOR 3D MEDICAL IMAGE SEGMENTATION
123
2 MATHEMATICAL MODELS IN IMAGE SEGMENTATION
124
3 SEMIIMPLICIT 3D COVOLUME SCHEME
130
4 BUILDING UP THE PARALLEL ALGORITHM
139
5 DISCUSSION OF COMPUTATIONAL RESULTS
149
6 ACKNOWLEDGMENTS
157
VOLUMETRIC SEGMENTATION USING SHAPE MODELS IN THE LEVEL SET FRAMEWORK
161
2 BRIEF MATHEMATICAL FORMULATION OF LEVEL SETS
163
3 BASIC APPLICATION OF LEVEL SET METHODS
166
4 ACTIVE CONTOURS IN THE LEVEL SET FRAMEWORK
174
5 IMAGE SEGMENTATION USING SHAPE PRIOR
186
6 CONCLUSIONS
203
7 ACKNOWLEDGMENTS
204
MEDICAL IMAGE SEGMENTATION BASED ON DEFORMABLE MODELS AND ITS APPLICATIONS
209
2 DEFORMABLE MODELS
217
3 TONGUE BODY EXTRACTION BASED ON A COLOR GVF SNAKE
222
4 TONGUE SEGMENTATION BASED ON A COLOR GVF SNAKE
227
5 CEREBRAL CORTEX MR IMAGE SEGMENTATION
231
6 PRIORBASED CARDIAC VALVE SEGMENTATION USING A GEODESIC SNAKE
248
7 REFERENCES
256
BREAST STRAIN IMAGING A CAD FRAMEWORK
261
1 INTRODUCTION
262
2 GENERAL ULTRASOUND IMAGE ANALYSIS ARCHITECTURE
263
4 THEORY OF FRONT EVOLUTION FOR BOUNDARY ESTIMATION OF LESION
266
5 2D CONTINUOUS STRAIN MODE SYSTEM
270
6 CONCLUSION
286
ALTERNATE SPACES FOR MODEL DEFORMATION APPLICATION OF STOP AND GO ACTIVE MODELS TO MEDICAL IMAGES
289
2 PROSTATE BOUNDARY SEGMENTATION FROM 2D TRUS IMAGES
327
3 TESTING AND OPTIMIZATION USING VIRTUAL OPERATORS
338
4 3D SEGMENTATION
346
5 SUMMARY AND DISCUSSION
364
6 REFERENCES
367
SEGMENTATION OF BRAIN MR IMAGES USING JDIVERGENCEBASED ACTIVE CONTOUR MODELS
371
2 METHODS
374
3 EXPERIMENTAL RESULTS
382
4 CONCLUSIONS AND FUTURE RESEARCH
386
5 ACKNOWLEDGMENTS
387
6 REFERENCES
390
MORPHOMETRIC ANALYSIS OF NORMAL AND PATHOLOGIC BRAIN STRUCTURE VIA HIGHDIMENSIONAL SHAPE TRANSFORMATIO...
393
2 SHAPE TRANSFORMATIONS AND DEFORMABLE REGISTRATION OF BRAIN IMAGES
397
3 VOXELBASED MORPHOMETRIC ANALYSIS
402
4 DEFORMABLE REGISTRATION OF BRAIN ATLASES TO BRAIN TUMOR IMAGES
412
5 CONCLUSION
439
6 ACKNOWLEDGMENTS
440
EFFICIENT KERNEL DENSITY ESTIMATION OF SHAPE AND INTENSITY PRIORS FOR LEVEL SET SEGMENTATION
447
2 LEVEL SET SEGMENTATION AS BAYESIAN INFERENCE
449
3 EFFICIENT NONPARAMETRIC STATISTICAL SHAPE MODEL
450
4 ENERGY FORMULATION AND MINIMIZATION
452
5 EXPERIMENTAL RESULTS AND VALIDATION
453
6 CONCLUSION
459
8 NOTES
460
VOLUMETRIC MRI ANALYSIS OF DYSLEXIC SUBJECTS USING A LEVEL SET FRAMEWORK
461
1 INTRODUCTION
462
2 THE NEUROANATOMY BACKGROUND
463
3 PROBLEM STATEMENT DATASET DESCRIPTION AND PROPOSED APPROACH
466
4 PROPOSED APPROACH
469
5 CONCLUSION
488
7 REFERENCES
490
ANALYSIS OF 4D CARDIAC MR DATA WITH NURBS DEFORMABLE MODELS TEMPORAL FITTING STRATEGY AND NONRIGID REGIS...
493
1 INTRODUCTION
494
2 NURBS MODEL
496
3 MATHEMATICAL PRELIMINARIES
500
4 MODEL FITTING AND NONRIGID REGISTRATION
504
5 LAGRANGIAN AND EULERIAN STRAIN MEASUREMENTS FROM AN NURBS MODEL
513
6 RESULTS
516
7 CONCLUSIONS
529
8 REFERENCES
532
ROBUST NEUROIMAGINGBASED CLASSIFICATION TECHNIQUES OF AUTISTIC VS TYPICALLY DEVELOPING BRAIN
535
1 INTRODUCTION
536
2 SUBJECTS AND IMAGE ACQUISITION
541
3 IMAGE PROCESSING AND ANALYSIS
543
4 PROPOSED CLASSIFICATION APPROACHES
555
5 DISCUSSION
562
6 REFERENCES
563
INDEX
567
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About the author (2007)

Aly A. Farag received the bachelor degree from Cairo University, Egypt and the PhD degree from Purdue University in Electrical Engineering. He also holds master degrees in bioengineering from the Ohio State and the University of Michigan. He is a University Scholar and Professor of Electrical & Computer Engineering at the University of Louisville. Dr. Farag is the founder and director of the Computer Vision and Image Processing Laboratory (CVIP Lab) which focuses on imaging science, computer vision and biomedical imaging. Dr. Farag main research focus is 3D object reconstruction from multimodality imaging, and applications of statistical and variational methods for object segmentation and registration. He has authored over 250 technical papers in the field of image understanding and holds a number patents. He is regular reviewer to a number of professional organizations in the United States and abroad, and a member of the editorial boards of a number journals and international meetings.

Jasjit S. Suri, PhD is an innovator, scientist, a visionary, and industrialist and an internationally known world leader in Biomedical Engineering and Biological Sciences. Dr. Suri has spent over 20 years in the field of biomedical engineering, devices and its management. He received his Doctorate from the University of Washinton, Seattle and Master's in Executive Business Management from Weatherhead, Case Western Reserve University, Cleveland, Ohio. Dr. Suri was crowned with the President's Gold Medal in 1980 and elected as a Fellow of the American Institute for Medical and Biological Engineering.

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